On Thu, 22 May 2003 15:33:30 +0200
Pedram Sendi <psendi@uhbs.ch> wrote:
> Dear All
>
> I am analysing the effect of a stable partnership (p.stable) adjusted for
> other co-variates on the ability to work (abilityrr) in HIV infected
> patients. Abilityrr has three ordinal categories (0,1,2) and I am modeling
> this using a proportional odds model using Harrell's Design library. Sex
> and log.rna (continous variable) do not operate in an ordinal fashion (see
> attached figure). How would I need to treat these co-variates in the model?
> Many thanks for your support!!!
>
> Best wishes,
> Pedram
>
>
>
> Pedram Sendi, MD, DSc
> Institute for Clinical Epidemiology & Division of Infectious Diseases
> Institut fur klinische Epidemiologie & Abteilung fur Infektiologie
> Basel University Hospital
> Kantonsspital Basel
> Hebelstrasse 10, 3rd Floor
> CH-4031 Basel
> Switzerland
> Phone: +41 61 265 31 02
> Fax: +41 61 265 31 09
> E-Mail: psendi@uhbs.ch
>
>
> -----Original Message-----
> From: Spencer Graves [SMTP:spencer.graves@PDF.COM]
> Sent: Tuesday, May 20, 2003 4:24 PM
> To: psendi@uhbs.ch
> Cc: s-news@lists.biostat.wustl.edu
> Subject: Re: [S] mergin subsets of dataframes
>
>
>
You sent a non-standard type of attachment that I couldn't read. At any rate,
the graphical diagnostics in my book Regression Modeling Strategies, along with
the comparison of the proportional odds and continuation ratio models, may
suggest something to you. If there are too many exceptions to these models'
assumptions you might just use a multinomial model as you have only 3
categories.
---
Frank E Harrell Jr Prof. of Biostatistics & Statistics
Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat
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